publish updates from main

content/guides/bake/index.md

@@ -32,16 +32,16 @@ This guide assumes that you're familiar with:
 
 ## Prerequisites
 
-- A recent version of Docker is installed on your machine.
-- Git is installed for cloning repositories.
+- You have a recent version of Docker installed on your machine.
+- You have Git installed for cloning repositories.
 - You're using the [containerd](/manuals/desktop/containerd.md) image store.
 
 ## Introduction
 
 This guide uses an example project to demonstrate how Docker Buildx Bake can
-streamline your build and test workflows. This repository includes both a
-Dockerfile and `docker-bake.hcl`, giving you a ready-to-use setup to try out
-Bake commands.
+streamline your build and test workflows. The repository includes both a
+Dockerfile and a `docker-bake.hcl` file, giving you a ready-to-use setup to try
+out Bake commands.
 
 Start by cloning the example repository:
 
@@ -114,7 +114,7 @@ $ docker buildx build \
 
 ## Testing and linting
 
-Bake isn't just for defining build configurations, and running builds. You can
+Bake isn't just for defining build configurations and running builds. You can
 also use Bake to run your tests, effectively using BuildKit as a task runner.
 Running your tests in containers is great for ensuring reproducible results.
 This section shows how to add two types of tests:
@@ -133,7 +133,7 @@ target "test" {
 ```
 
 > [!TIP]
-> Using the `type=cacheonly` ensures that the build output is effectively
+> Using `type=cacheonly` ensures that the build output is effectively
 > discarded; the layers are saved to BuildKit's cache, but Buildx will not
 > attempt to load the result to the Docker Engine's image store.
 >
@@ -145,7 +145,7 @@ you'll receive an error indicating that the `test` stage does not exist in the
 Dockerfile.
 
 ```console
-$ docker buildx bake bake test
+$ docker buildx bake test
 [+] Building 1.2s (6/6) FINISHED
  => [internal] load local bake definitions
 ...
@@ -252,13 +252,12 @@ combinations to build:
 
 The `matrix` attribute defines the variants to build ("release" and "debug").
 The `name` attribute defines how the matrix gets expanded into multiple
-distinct build targets. In this case, it's relatively simple. The matrix
-attribute expands the build into two workflows: `image-release` and
-`image-debug`, each using different configuration parameters.
+distinct build targets. In this case, the matrix attribute expands the build
+into two workflows: `image-release` and `image-debug`, each using different
+configuration parameters.
 
-Next, when building the development variant, we'll pass in a `BUILD_TAGS`
-argument with the value of the matrix variable, which we'll later consume in
-the Dockerfile.
+Next, define a build argument named `BUILD_TAGS` which takes the value of the
+matrix variable.
 
 ```diff {title="docker-bake.hcl"}
    target = "image"
@@ -365,7 +364,7 @@ bakeme:latest           20065d2c4d22       44.4MB         25.9MB
 
 Exporting build artifacts like binaries can be useful for deploying to
 environments without Docker or Kubernetes. For example, if your programs are
-meant to be run on user's local machine.
+meant to be run on a user's local machine.
 
 > [!TIP]
 > The techniques discussed in this section can be applied not only to build
@@ -502,7 +501,7 @@ multi-platform builds, testing, and artifact export. By integrating Buildx Bake
 into your projects, you can simplify your Docker builds, make your build
 configuration portable, and wrangle complex configurations more easily.
 
-Experiment with different configurations and extend your Bake files to match
+Experiment with different configurations and extend your Bake files to suit
 your project's needs. You might consider integrating Bake into your CI/CD
 pipelines to automate builds, testing, and artifact deployment. The flexibility
 and power of Buildx Bake can significantly improve your development and

content/guides/jupyter.md

@@ -383,39 +383,42 @@ $ docker run --rm -p 8889:8888 YOUR-USER-NAME/my-jupyer-image start-notebook.py
 
 ### Share your volume
 
-This example uses the Docker Desktop [Volumes Backup & Share](https://hub.docker.com/extensions/docker/volumes-backup-extension) extension. Alternatively, in the CLI you can [back up the volume](/engine/storage/volumes/#back-up-a-volume) and then [push it using the ORAS CLI](/manuals/docker-hub/oci-artifacts.md#push-a-volume).
-
-1. Install the Volumes Backup & Share extension.
-
-   1. Open the Docker Dashboard and select **Extensions**.
-   2. Search for `Volumes Backup & Share`.
-   3. In the search results select **Install** for the extension.
-
-2. Open the **Volumes Backup & Share** extension in the Docker Dashboard.
-3. Next to the **jupyter-data** volume, select the **Export volume** icon.
-4. In the **Export content** window, select **Registry**.
-5. In the text box under **Registry**, specify your Docker ID and a name for the
-   volume. For example, `YOUR-USERNAME/jupyter-data`.
-6. Select **Export**.
-7. Verify that you exported the volume to Docker Hub.
+This example uses the Docker Desktop graphical user interface. Alternatively, in the command line interface you can [back up the volume](/engine/storage/volumes/#back-up-a-volume) and then [push it using the ORAS CLI](/manuals/docker-hub/oci-artifacts.md#push-a-volume).
+
+1. Sign in to Docker Desktop.
+2. In the Docker Dashboard, select **Volumes**.
+3. Select the **jupyter-data** volume by selecting the name.
+4. Select the **Exports** tab.
+5. Select **Quick export**.
+6. For **Location**, select **Registry**.
+7. In the text box under **Registry**, specify your Docker ID, a name for the
+   volume, and a tag. For example, `YOUR-USERNAME/jupyter-data:latest`.
+8. Select **Save**.
+9. Verify that you exported the volume to Docker Hub.
    1. Go to [Docker Hub](https://hub.docker.com).
    2. Select **Repositories**.
    3. View the **Last pushed** time for your repository.
 
 Other users can now download and import your volume. To import the volume and then run it with your image:
 
-1. In the Volumes Backup & Share extension, select **Import into new volume**.
-2. In the **Import into a new volume** window, select **Registry**.
-3. In the text box under **Registry**, specify your Docker ID and the repository
-   name for the volume. For example, `YOUR-USERNAME/jupyter-data`.
-4. In **Volume name**, specify the name you want to give the
-   volume. This example uses `jupyter-data` as the name.
-5. Select **Import**.
-6. In a terminal, run `docker run` to run your image with the imported volume.
+1. Sign in to Docker Desktop.
+2. In the Docker Dashboard, select **Volumes**.
+3. Select **Create** to create a new volume.
+4. Specify a name for the new volume. For this example, use `jupyter-data-2`.
+5. Select **Create**.
+6. In the list of volumes, select the **jupyter-data-2** volume by selecting the
+   name.
+7. Select **Import**.
+8. For **Location**, select **Registry**.
+9. In the text box under **Registry**, specify the same name as the repository
+   that you exported your volume to. For example,
+   `YOUR-USERNAME/jupyter-data:latest`.
+10. Select **Import**.
+11. In a terminal, run `docker run` to run your image with the imported volume.
    Replace `YOUR-USER-NAME` with your Docker ID.
 
    ```console
-   $ docker run --rm -p 8889:8888 -v jupyter-data:/home/jovyan/work YOUR-USER-NAME/my-jupyter-image start-notebook.py --NotebookApp.token='my-token'
+   $ docker run --rm -p 8889:8888 -v jupyter-data-2:/home/jovyan/work YOUR-USER-NAME/my-jupyter-image start-notebook.py --NotebookApp.token='my-token'
    ```
 
 ## Summary

content/manuals/security/for-admins/access-tokens.md

@@ -12,8 +12,12 @@ The organization access tokens feature is currently in [Beta](../../release-life
 
 > [!WARNING]
 >
-> Organization access tokens aren't currently compatible with Docker Build Cloud. If you
-> are using Docker Build Cloud, you must use personal access tokens instead.
+> Organization access tokens aren't currently compatible with the following services:
+>
+> - Docker Build Cloud
+> - Docker Scout
+>
+> If you use these services, you must use personal access tokens instead.
 
 An organization access token (OAT) is like a [personal access token
 (PAT)](/security/for-developers/access-tokens/), but an OAT is associated with